Academic journal article Educational Technology & Society

Knowledge Visualization for Self-Regulated Learning

Academic journal article Educational Technology & Society

Knowledge Visualization for Self-Regulated Learning

Article excerpt

Introduction

Due to its flexibility in delivery and just-time access, e-learning has been widely adopted in recent years. In e- learning applications, learners are encouraged to learn through interacting with a wide range of resources to acquire and build their knowledge. While such a resource-abundant and self-regulated learning environment allows learners a great deal of freedom and flexibility in searching for, selecting, and assembling information, learners may suffer from cognitive overload and conceptual and navigational disorientation when faced with massive information online (Tergan, 2005; Kayama & Okamoto, 2001; Miller & Miller, 1999). The challenge is even greater when learning contents are scattered under disparate topics and complex knowledge structures. When faced with this problem, many learners are unable to figure out features and meaningful patterns of various kinds of information, and are easily hampered by limited working memory. This is mainly because novices lack sufficient knowledge and a deep understanding of the subject domain, which is crucial to organizing information and knowledge for retention in long-term memory. Also, traditional education breaks wholes into parts, and focuses separately on each part, and learners are often unable to create the big picture before all the parts are presented. As a result, most online learners, especially novices, become "lost-in-hyperspace".

This study aims to improve the design of current e-learning systems by dealing with the aforesaid problem. To facilitate cognitive processing and self-regulated learning, learners should be supported with appropriate learning strategies, among which cognitive and meta-cognitive strategies have been well identified (Bransford, 2000, Zimmerman, 2000; Winne, 2001). Learners are helped in their independent learning if they have conceptual knowledge, and learners can become more independent if they have awareness of their own knowledge and ability to understand, control, and manipulate individual learning processes. While these strategies have been found to be effective, few studies have examined how these strategies can be implemented in instructional design, especially in online learning environments. While learning theories or strategies offer guidelines of improving the design of current e-learning systems, it is far more difficult and additional effort is needed to explore effective instructional methods (Reigeluth, 1999).

This study investigates a knowledge visualization (KV) approach to support resource-abundant and self-regulated online learning, which consists of three components. First, an explicit representation of conceptual knowledge structure is constructed by capturing key knowledge concepts and their relationships in a visual format. This visualized knowledge structure serves as a cognitive roadmap to facilitate the knowledge construction and high level thinking of online learners. Second, abstract concepts are connected with concrete contents by linking knowledge concepts with learning resources. In this way, information processing and knowledge construction, the two key aspects of the learning process, are well integrated. Learners can easily navigate throughout the resource-abundant, non-linear knowledge space aided by the visualized cognitive roadmap. Third, meta-cognitive learning support is provided for learners to regulate and plan their learning process. Assessment materials associated with knowledge concepts are provided for self-evaluation of learning outcomes in granular knowledge components, from which the system generates feedback and guides individuals throughout their learning process.

To implement the proposed approach, an online learning system was developed using computer and Web-based technologies. The system has been designed to help learners transcend the limitations of their minds, not only in cognitive processing, but also in high level thinking and knowledge construction. …

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